Neural Correlates of Memory-Based Generalization in Humans - PROJECT SUMMARY The ability to generalize from prior experience is a cornerstone of human cognition. In daily life, people make accurate predictions in unfamiliar situations without needing to encounter every possible scenario. For example, when visiting a new supermarket, one can often anticipate where items are located by generalizing from the layout of previously visited stores. However, impairments in generalization can severely disrupt cognitive and functional abilities. In neuropsychiatric conditions such as PTSD, schizophrenia, and Alzheimer’s disease, individuals may overgeneralize threats or struggle to transfer learned knowledge in new situations, leading to deficits in inference, reasoning, and decision-making. Despite the importance of this cognitive process, the neural mechanisms underlying generalization remain poorly understood. Theoretical work suggests that generalization relies on internal models that guide predictions in novel contexts. Both theoretical models and supporting animal research point to the hippocampus and prefrontal cortex as key regions in this cognitive process. Building on this foundation, I hypothesize that generalization is supported by coordinated hippocampal-prefrontal dynamics, in which learned structure (i.e., schemas) represented in the prefrontal cortex guide hippocampal predictions to minimize prediction error in novel contexts. To test this, the project will leverage rare intracranial recordings of single neuron activity and local field potentials from patients who are implanted with depth electrodes for seizure monitoring while they engage in a memory-based prediction task. Participants will view naturalistic videos depicting everyday activities and will predict what happens next at key transition points between events (i.e., event boundaries). The task includes conditions that vary in visual similarity and event structure, allowing researchers to probe how people generalize learned temporal patterns to new contexts. Aim 1 will test whether changes in spike rate and spike phase for neurons responsive to event boundaries predict successful generalizations. Aim 2 will assess whether the reinstatement of neural patterns associated with learned event sequences and prefrontal-hippocampal theta-band synchrony support generalization. Together, these aims will probe the mechanisms that support generalization in novel contexts. The candidate will receive comprehensive training in systems neuroscience, neural data analysis, scientific communication, and professional development under the mentorship of Drs. Jie Zheng (primary sponsor), Jack Lin (co-sponsor), Ueli Rutishauser, and Julia Sharma. This training includes structured mentorship, hands-on experience with human neural recordings, national workshops and conferences, and engagement in patient care. In addition, UC Davis offers an exceptional research and training environment to support the candidate’s development as a surgeon-scientist dedicated to advancing care for individuals with cognitive disorders.
